The present invention is directed to an apparatus and method for enhancing a video signal and, more specifically, to an apparatus and method for measuring and filtering noise signals in an active video signal to create an enhanced video signal that produces a video image that is subjectively perceived to be superior to prior art video images.
Video signal image enhancement circuitry in current television sets provides image enhancement by using noise measurement algorithms to measure and filter out noise signals. In the world of analog signals, the most common type of noise is Gaussian noise. Therefore, most prior art noise measurement algorithms are designed to measure and filter out only Gaussian noise.
Because noise on the video signal may arise from more than one source, noise that is detected in the video signal may be composed of more than one component. Each noise signal component may have its own characteristics. This is true even for noise signal components that are of the same type. For example, even if all the noise signal components in a video signal are of the Gaussian noise type, the frequency characteristics of each Gaussian noise signal component will differ from the frequency characteristics of each of the other Gaussian noise signal components.
With the level of digital transmissions in the environment continually increasing, digital transmission MPEG artifacts are more commonly appearing in video signals. To maintain high quality video signals, it is desirable to eliminate the effect of the MPEG artifacts upon the video signals. Because the existing noise measurement algorithms in current television sets can only measure Gaussian noise, it is necessary to add a separate MPEG artifact detector to the television set circuitry to detect, measure and eliminate MPEG artifacts from the video signal.
It would be desirable to have an apparatus and method that is capable of detecting more than one Gaussian noise signal component in a video signal. In addition, it would be desirable if the apparatus and method is also capable of detecting MPEG artifact noise signal components in a video signal.
To reduce noise in a video signal the noise level in the video signal must be identified and then subtracted from the video signal. A number of prior art techniques exist for identifying the noise level in a video signal. For example, a simple measure of the root-mean-square (xe2x80x9crmsxe2x80x9d) noise in a video signal may be obtained from the following equation:                               N          estimated                =                                            ∑              i                        ⁢                                          {                                                      (                                                                  s                        ⁡                                                  [                          i                          ]                                                                    +                                              n                        ⁡                                                  [                          i                          ]                                                                                      )                                    -                                      s                    ⁡                                          [                      i                      ]                                                                      }                            2                                                          (        1        )            
In Equation (1), Nestimated is the estimated noise, s[i] is the signal without noise in the ith interval, and n[i] is the noise is the ith interval. Because the received signal is (s[i]+n[i]), the measurement of Nestimated can only be obtained when s[i] is known. This suggests the possibility of measuring the noise in the horizontal blanking intervals (or the vertical blanking intervals) of the video signal where s[i] is known to be equal to a blanking level Vbl. Although the blanking level Vbl is not known exactly, it can be estimated as the long term average of (s[i]+n[i]) in the blanking interval.
Unfortunately, the estimate of the noise level in the blanking interval is not a reliable estimate of the noise level in the active video signal. This is because blanking signals are frequently reinserted by videocassette recorders and signal repeater stations in order to minimize clamp noise and sync jitter. That is, new blanking signals with less noise are inserted in place of the old blanking signals that may have more noise. The noise in the newly inserted blanking signals may therefore be less than the noise actually contained in the active video signal. Equating the noise level in the newly inserted blanking signals with the noise level in the active video signal would result in an underestimation of the actual noise level in the active video signal.
For this reason it is necessary to measure the noise level in the active video signal portion of the video signal. This introduces the problem of distinguishing between the signal and the noise in the active video signal. One approach for addressing this problem has been to assume that the image contains a certain minimum amount of horizontal stretches of constant luminance. In each of these stretches of L pixels having constant luminance (or almost constant luminance), it is assumed that variations within these stretches of pixels are caused by noise. It is possible to estimate the level of these local noise signals by determining the variance as follows:                               N          estimated                =                              (                          x              ,              y              ,              f                        )                    =                                    ∑                              j                =                x                                            x                +                L                -                1                                      ⁢                          xe2x80x83                        ⁢                                          (                                                      F                    ⁡                                          [                                              j                        ,                        y                        ,                        f                                            ]                                                        -                                      F                                          x                      ,                      y                      ,                      f                                                                      )                            2                                                          (        2        )            
In Equation (2), a pixel position is specified by the coordinates (x,y,f). For a particular pixel, the value xe2x80x9cxxe2x80x9d specifies the position of the pixel in a line, the value xe2x80x9cyxe2x80x9d specifies the position of the line in a frame, and the value xe2x80x9cfxe2x80x9d specifies the position of the frame. During a broadcast the pixels are transmitted sequentially. Therefore, the location of any particular pixel during a transmission may be specified by a single (i.e., one dimensional) coordinate. The single coordinate is referred to as xe2x80x9cixe2x80x9d and the value of xe2x80x9cixe2x80x9d is calculated by:
i=xxc2x7Tx+yxc2x7TL+fxc2x7Tfxe2x80x83xe2x80x83(3)
In Equation (3), Tx is the sample time, TL is the line duration and Tf is the field duration. The values for Tx, TL and Tf are fixed for a particular standard (e.g., PAL, NTSC). The location of a pixel in a transmission may be specified using this method.
In Equation (2), Nestimated (x,y,f) is the estimated noise, L is the number of pixels in a selected stretch of pixels, and F[x,y,f] is equal to (Y[i]+n[i]). Y[i] is the luminance in the ith interval and n[i] is the noise is the ith interval. In Equation(2), Fx,y,f is the local average of the (Y[i]+n[i]) signal and is calculated by:                               F                      x            ,            y            ,            f                          =                              1            L                    ⁢                                    ∑                              k                =                x                                            x                +                L                -                1                                      ⁢                          xe2x80x83                        ⁢                          F              ⁡                              [                                  k                  ,                  y                  ,                  f                                ]                                                                        (        4        )            
To utilize the variance method to estimate the noise level in an active video signal it is necessary to calculate the variance from a large number of areas. It is assumed that the image contains a certain amount of small areas of constant luminance. It is also assumed that the areas yielding the smallest variance contain no detail from the image but only noise. The problem is that if the image contains a lot of xe2x80x9cflatxe2x80x9d area (where there is no contrast or very little contrast in the image), the variance method leads to an underestimation of the noise. This makes the noise measurement dependent upon the picture content.
One method for solving this problem is to take the average of the noise estimates over the R smallest noise estimates where R is a preselected number that is a non-zero positive integer. The averaging of the noise estimates decreases the dependency of the noise measurement upon the picture content.
After a noise measurement system estimates the amount of noise in a video signal, the noise measurement system sends the noise estimate to other signal processing elements of the video system. One such signal processing element is a noise subtraction element that is capable of subtracting the noise components of the signal from the active video signal. The subtraction of the noise components from the active video signal provides an enhanced active video signal that is capable of producing improved video images with less noise content.
The presence in a video signal of noise components having differing frequency characteristics may cause a noise measurement system (and its associated noise subtraction element) to make corrections to the video signal that do not provide the highest quality image possible from the viewpoint of subjective perception. The subjective perception of viewers of the video image that is provided by the corrected video signal may not always be as good as one would expect based on the corrections applied by a noise measurement system. This is because presently existing noise measurement methods are not designed to remove noise from video signals in a manner that would optimize the resulting video images for presentation to the human eye.
Therefore, there is a need for noise measurement apparatuses and methods that are capable of measuring and filtering noise signals in video signals in a manner that takes into account the properties of the human eye. In a particular, there is a need for noise measurement apparatuses and methods that are capable of measuring and filtering noise signals in video signals in a manner that provides an enhanced video image that is subjectively perceivable by human viewers as having image qualities that are superior compared to the image qualities of video images produced with prior art noise measurement algorithms. More particularly, there is a need for a noise measurement apparatuses and methods that are capable of determining whether noise in a video signal is sufficiently large to be noticed by the human eye.
The present invention generally comprises an apparatus and method for measuring and filtering noise signals in an active video signal in a manner that takes into account the properties of the human visual system that are used to view video images.
In an advantageous embodiment of the invention, the apparatus of the invention comprises (1) a filter that is capable of selecting a range of frequency components of a video signal to form a filtered video signal, and (2) an absolute value unit that is capable of forming a signal that represents the absolute value of the luminance of pixels in the filtered video signal, and (3) a clipping unit that is capable of clipping the signal that represents the absolute value of the luminance of the pixels to a clipping threshold value related to subjective human perception abilities, and (4) a summer circuit that is capable of summing the values of the clipped signals for pixels that are located within a sliding window, wherein the summer circuit is capable of obtaining a plurality of the sums of the values as the sliding window is sequentially located in different areas of a frame of the video image, and (5) a detector that is capable of detecting at least one sum of the values that is a minimum value of the plurality of the sums of the values, to obtain a signal that is indicative of the noise in the video signal of the video image.
It is a primary object of the present invention to provide a noise measurement apparatus and that is capable of measuring and filtering noise signals in video signals in a manner that takes into account the properties of the human visual system that are used to view video images.
It is a further object of the present invention to provide a noise measurement apparatus and method that is capable of measuring and filtering noise signals in active video signals in a manner that provides an enhanced video image that is subjectively perceivable by human viewers as having image qualities that are superior compared to the image qualities of video images produced with prior art noise measurement apparatus and methods.
The foregoing has outlined rather broadly the features and technical advantages of the present invention so that those skilled in the art may better understand the Detailed Description of the Invention that follows. Additional features and advantages of the invention will be described hereinafter that form the subject of the claims of the invention. Those skilled in the art should appreciate that they may readily use the conception and the specific embodiment disclosed as a basis for modifying or designing other structures for carrying out the same purposes of the present invention. Those skilled in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the invention in its broadest form.
Before undertaking the Detailed Description of the Invention, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document: the terms xe2x80x9cincludexe2x80x9d and xe2x80x9ccomprisexe2x80x9d and derivatives thereof, mean inclusion without limitation; the term xe2x80x9cor,xe2x80x9d is inclusive, meaning and/or; the phrases xe2x80x9cassociated withxe2x80x9d and xe2x80x9cassociated therewith,xe2x80x9d as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like; and the term xe2x80x9ccontroller,xe2x80x9d xe2x80x9cprocessor,xe2x80x9d or xe2x80x9capparatusxe2x80x9d means any device, system or part thereof that controls at least one operation, such a device may be implemented in hardware, firmware or software, or some combination of at least two of the same. It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. Definitions for certain words and phrases are provided throughout this patent document, those of ordinary skill in the art should understand that in many, if not most instances, such definitions apply to prior, as well as future uses of such defined words and phrases.